United States Office of Office of Solid EPA/540/4-91/003

Environmental Protection Research and Waste

Development

March 1991

and Emergency

Response

Ground-Water Issue

CHARACTERIZING SOILS FOR

HAZARDOUS WASTE SITE ASSESSMENTS

R. P. Breckenridgel, J. R. Williams2, and J. F. Keckl

INTRODUCTION

The Regional Superfund Ground Water

Forum is a group of ground-water scentists

representing EPA’s Regional Offices, organized to exchange up-to-date information related to ground-water remediation at hazardous waste sites. Soil characterization at

hazardous waste sites is an issue identified by

the forum as a concern of CERCLA decisionmakers.

To address this issue, this paper was prepared through support from EMSL-LV and

RSKERL, under the direction of R. P.

Breckenridge, with the support of the

Superfund Technical Support Project For

further information contact Ken Brown, EMSLLV Center Director, at FTS 545-2270 or R. P.

Breckenridge at FTS 583-0757.

Site investigation and remediation under the

Superfund program is performed using the

CERCLA remedial investigation/feasibility

study (RI/FS) process. The goal of the RI/FS

process is to reach a Record of Decision

(ROD) in a timely manner. Soil characterization provides data types required for decision

making in three distinct RI/FS tasks:

1..

2.

3.

Determination of the nature and extent of

soil contamination.

Risk assessment, and determination of

risk-baaed soil dean-up levels.

Determination of the potential effectiveness of soil remediation alternatives.

Identification of data types required for the first

task, determination of the nature and extent of

contamination, is relatively straight forward.

The nature of contamination is related to the

types of operations conducted at the site.

Existing records, if available, and interviews

with personnel familiar with the site history are

good sources of information to help determine

the types of contaminants potentially present.

This information may be used to shorten the

Iist of target analytes from the several hundred

contaminants of concern in the 40 CFR Part

284 list (Date 7-l-89). Numerous guidance

documents are available for planning all

1 ldaho National Engineering Laboratory, Environmental Science and Technology Group, Idaho Falls, ID 83415. 

2 Soil Scientist, U.S. EPA/R.S. Kerr Environmental Research Laboratory, Ada, OK 74820

SuperfundTechnology Support Center for Monitoring

and Site Characterization, Environmental Monitoring

Systems Laboratory Las Vegas, NV

Superfund Technoloqy Support Center for

Ground-Water Fate and Transport, Robert S. Kerr

Environmental Research Laboratory Ada, OK

Agency
aspects of the subsequent sampling effort (US EPA 1987a,

1988a, 1988b, and Jenkins et at., 1988).

The extent of contamination is also related to the types of

operations conducted at the site. Existing records, if available,

and interviews with personnel familiar with the site history are

aIso good sources of information to help determine the extent of

contamination potentially present. The extent of contamination

is dependent on the nature of the contaminant source(s) and the

extent of contaminant migration from the source(s). Migration

routes may include air, via volatilization and fugitive dust emissions; overland flow; direct discharge; Ieachate migration to

ground water and surface runoff and erosion. Preparation of a

preliminary siteconceptual model is therefore an important step

in planning and directing the sampling effort The conceptual

model should identify the most likely locations of contaminants

in soil and the pathways through which they move.

The data type requirements for tasks 2 and 3 are frequently less

well understood. Tasks 2 and 3 require knowledge of both the

nature and extent of contamination, the environmental fate and

transport of the contaminants, and an appreciation of the need

for quality data to select a viable remedial treatment technique.

Contaminant fate and transport estimation is usually performed

by computer modeling. Site-specific information about the soils

in which contamination occurs, migrates, and interacts with, is

required as input to a model. The accyof the model output

is no better than the accuracy of the input information.

The purpose of this paper is to provide guidance to Remedial

Project Managers (RPM) and On-Scene Coordinators (OSC)

ooncerning soil characterization data types required for

decision-making in the CERCLA RI/FS process related to risk

assessment and remedial alternative evaluation for contaminated soils. Many of the problems that arise are due to a lack of

understandng the data types required for tasks 2 and 3 above.

This paper describes the soil chactererization data types required to conduct model based risk assessment for task 2 and

the selection of remedial design for task 3. The information

presented in this paper is a compilation of current information

from the literature and from experience combined to meet the

purpose of this paper.

EMSL-Las Vegas and RSKERL-Ada convened a technical

committee of experts to examine the issue and provide technical

guidance based on current scientific information. Members of

the cornmittee were Joe R. Williams, RSKERL-Ada; Robert G.

Baca, Robert P. Breckenridge, Alan B. Crookett and John F.

Keck from the Idaho National Engineering Laboratory, Idaho

Falls, ID; Gretchen L Rupp, PE, University of Nevada-Las

Vegas; and Ken Brown, EMSL-LV.

This document was compiled by the authors and edited by the

members of the committee and a group of peer reviewers.

Characterization of a hazardous waste site should be done

using an integrated investigative approach to deterrnine quickly

and cost effectively the potential health effects and approach

response measures at a site. An integrated approach involves

consideration of the different types and sources of contaminants, their fate as they are transported through and are partitioned, and their impact on different parts of the environment.

This paper addresees two ooncerns related to soil characterization for CERCLA remedial response. The first concern is the

applicability of traditional soil declassification methods to CERCLA

soil characterization. The second is the identification of soil

characterization data types required for CERCLA risk assessment and analysis of remedial alternatives. These concerns are

related, in that the Data Quality Objective (DQO) process

addresses both. The DQO process was developed, in part, to

assist CERCLA decision-makers in identifying the data types,

data quality,and data quantity required to support decisions that

must be made during the RI/FS process. Data Quality Objectives for Remedial Response Activities: DevelopmentProcess

(US EPA 1987b) is a guidebook on developing DQOs. This

process as it relates to CERCLA soil characterization is discussed in the Data Quality Objective section of this paper.

Data types required for soil oharacterization must be determined

early in the RI/FS process, using the DQO process. Often, the

first soil data types related to risk assessment and remedial

alternative selection available during a CERCLA site investigation are soil textural descriptions from the borehole logs prepared by a geologist during investigations of the nature and

extent of contamination. These boreholes might include instalIation of ground-water monitoring wells, or soil boreholes. Typically, borehole logs contain soil Iithology and textural descriptions, based on visual analysis of drill cuttings.

Preliminary site data are potentially valuable, and can provide

modelers and engineers with data to begin prepare

conceptual model and perform scoping calculations. Soil texture affects movement of air and water in soil, infiltration rate,

porosity, water holding capacity, and other parameters.

Changes in lithology identify heterogeneities in the subsurface

(i.e., Iow permeability layers, etc.). Soil textural declassification is

therefore importantto contaminant fate and transport modeling,

and to screening and analysis of remedial alternatives. However, unless collected properly, soil textural descriptions are of

limited value for the following reasons:

1.

2.

3.

There are several different systems for classification of soil

particles with respect to size. To address this problem it is

important to identify which system has been or will be used

to classify a soil so that data can be properly compared.

Figure 1 can be used to compare the different systems (Gee

and Bauder, 1986). Keys to Soil Taxonomy (Soil Survey

Staff, 1990) provides details to one of the more useful

systems that should be consulted prior to classifying a site’s

soils.

The accuracy of the field classification is dependent on the

skill of the observer .To overcome this concern RPMs and

OSCs should collect soil textural data that are quantitative

rather than qualitative. Soil texture can be determined from

a soil sample by sieve analysis or hydrometer. These data

types are superior to qualitative description based on visual

analysis and are more Iikely to meet DQOs.

Even if the field person accurately classifies a soil (e.g., as

a silty sand or a sandy loam), textural descriptions do not

afford accurate estimations of actual physical properties

required for modeling end remedial alternative evaluation,

2

Concerns
such as hydraulic conductivity. For exarnple, the hydraulic

conductivity of silty-sand can range from 10-5 to 10-1 cm/sec

(four orders of magnitude).

These ranges of values maybe used for bounding calculations,

or to assist in preparation of the preliminary conceptual model.

These data may therefore meet DQOs for initial screening of

remedial alternatives, for example, but will Iikely not meet DQOs

for detailed analysis of alternatives.

DATA QUAILITY OBJECTIVES

EPA has developed the Data Quality Objective (DQO) process

to guide CERCLA site characterization. The relationship between CERCLA RI/FS activities and the DQO process is shown

in Figure 2 (US EPA 1988c, 1987a). The DQO process occurs

in three stages:

● Stage 1. Identify Decision Types. In this stage the types of

decisions that must be made during the RI/FS are identified.

1

USDA-U.S. DEPARTMENT OF AGRICULTURE, (SOIL SURVEY STAFF, 1975)

CCS - CANADA SOIL SURVEY COMMITTEE (McKEAGUE 1979)

ISSS-INTERNATIONAL SOIL SCI. SOC. (YONG AND WARKENTIN, 1966)

ASTM-AMERICAN SOCIETY FOR TESING & MATERIALS (ASTM, D-2487, 1985a)

Figure 1. Particle size limits according to several current

classification schemes (Gee and Bauder, 1986).

●

●

The types of decisions vary throughout the RI/FS process, but

in general they become increasingly quantitative as the process proceeds. During this stage it is important to identify and

involve the data users (e.g. modelers, engineers, and scientists), evaluate available data, develop a conceptual site

model, and specify objectives and decisions.

Stage 2. Identify Data Uses/Needs. In this stage data uses

are defined. This includes identification of the required data

types, data quality and data quantity required to make decisions on how to:

- Perform risk assessment

- Perform contaminant fate and transport modeling

- Identify and screen remedial alternatives

Stage 3. Design Data Collection Program. After Stage 1 and

2 activities has been defined and reviewed, a data collection

program addressing the date types, data quantity (number of

samples) and data quality required to make these decisions

needs to be developed as part of a sampling and analysis

plan.

Although this paper focuses on data types required for decisionmaking in the CERCLA RI/FS process related to soil contamination, references are provided to address date quantity quality

issues.

Data Types

The OSC or RPM must determine which soil parameters are

needed to make various RI/FS decisions. The types of decisions to be made therefore drive selection of data types. Data

types required for RI/FS activities including risk assessment,

contaminant fate and transport modeling and remedial alternative selection are discussed in Soil characteristics Data Types

Required for Modeling Section, and the Soil Characterization

Data Type Required for Remedial Alternative Selection Section.

Data Quality

The RPM or OSC must decide "HOW good does the data need

to be in order for me to make a given decision?”. EPA has

assigned quality levels to different RI/FS activities as a guideline. Data Quality Objectives for Remedial Response Activities

(US EPA, 1987a) offers guidance on this subject and contains

many useful references.

Data Quantity

The RPM or OSC must decide “How many samples do 1 need to

determine the mean and standard deviation of a given parameter at a given site?, or "How does a given parameter vary

spatially across the site?-. Decisions of this type must be

addressed by statistical design of the sampling effort. The Soil

SamplingQualityAssurance Guide (Barth et al., 1989) and Data

Quality Objectives for Rernedial Response (US EPA, 1987a)

offer guidance on this subject and contain many useful references.

3
Figure2. Phased RI/FS

4
.

IMPORTANT SOIL CHARACTERISTICS IN SITE

EVALUATION

Tables 1 and 2 identify methods for collecting and determining

data types for soil characteristics either in the field, laboratory

or by calculation. Soil characteristics in Table 1 are considered

the primary indicators that are needed to complete Phase I of the

RI/FS process. This is a short but concise list of oil data types

that are needed to make CERCLA decisions and should be

planned for and collected early in the sampling effort. These

primary types should allow for the initial screening of

remedial treatment alternatives and preliminary modeling of the

site for risk assessment. Many of these characteristics can be

obtained relatively inexpensively during periods of early field

work when the necessary drilling and sampling equipment are

already on site. Investigators should plan to collect data for all

the soil characteristics at the same locations and times soil

boring is done o install monitoring wells. Geophysical logging of

the well should also reconsidered as a cost effective method for

collecting lithologic information prior to casing the well. Data

quality and quantity must also be considered before beginning

collection of the appropriate data types.

The soil characteristics in Table 2 are considered ancillary only

because they are needed in the later stages and tasks of the

DQO process and the RI/FS process. If the site budget allows,

collection of these data types during early periods of field work

will improve the database available to make decisions on

remedial treatment selection and model-based risk assessments, Advanced planning and knowledge of the need for the

ancillary soil characteristics should be factored into early site

work to reduce overall costs and the time required to reach a

ROD. A small additional investment to collect ancillary data

during early site visits is almost slways more cost effective than

having to send crews back to the field to conduct additional soil

sampling.

Further detailed descriptions of the soil characteristics in Tables

1 and 2 can be found in Fundamentals of Soil Physics and Applications of Soil Physics (Hillel, 1980) and in a series of articles

by Dragun (1988, 1988a, 1988b). These references provide

excellent discussions of these characteristics and their influence on water movernent in soils as well as contaminant fate and

transport.

SOIL CHARACTERISTICS DATA TYPES REQUIRED

FOR MODELING

The information presented here is not intended sea review of all

data types required for all models, instead it presents a sampling

of the more appropriate models Used in risk assessment and 

remedial design.

UseS of Vadose Zones Models for CERCLA Remedial

Response Activities

Models are used in the CERCLA RI/FS process to estimate

contaminant fate and transport. These estimates of contaminant behavior in the environment are subsequently used for:

● Risk assessment. Risk assessment includes contaminant

release assessment exposure assessment, and determining

risk-based dean-up levels. Each of these activities requires

estimation of the rates and extents of contaminant movement

in the vadose zone, and of transformation and degradation

processes.

● Effectiveness assessment of remedial alternatives. This

task may also require determination of the rates and extents

of contaminant movement in the vadose zone, and of rates

and extents of transformation and degradation processes.

Technology-specifk data requirements are cited in the Soil

Characterization Data Type Required for Remedial Alternative selection Section.

The quantities, and quality of site characterization data

required for modeling should be carefully considered during RI/

FS scoping. Several currently available vadose zone fate and

transport modeIs are listed in Table 3. Soil characterization data

types required for each model are induded in the table. Model

documentation should be consulted for specific questions concerning uses and applications.

The Superfund Exposure Assessment Manual discusses various vadose zone models (US EPA, 1988e). This document

should be consulted to select codes that are EPA-approved.

Data Types Required for Modeling

Soil characterization data types required for modeling are included in Tables 1 and 2. Most of the models are one- or

two-dimensional solutions to the advection dispersion equation, applied to unsaturated flow. Each is different in the extent

to which transformation and degradation processes may be

simulated; various contaminant release scenarios are accommodated; heterogeneous soils and other site-specific characteristics are accounted for. Each, therefore, has different data

type input requirements.

All models require physicochemical data for the contaminants of

concern. These data are available in the literature, and from

EPA databases (US EPA, 1988c,d). The amount of physiochemical data required is generally related to the complexity of

the model. The models that account for biodegradation of

organics, vapor phase diffusion and other processes require

more input data than the relatively simpler transport models.

Data Quality and Quantity Required for Modeling

DQOs for the modeling task should be defined during RI/FS

scoping. The output of any computer model is only as valid as

the quality of the input data and code itself. Variance may result

from the data collection methodology or analytical process, or as

a result of spatial variability in the soil characteristic being

measured.

In general, the physical and chemical properties of soils vary

spatially. This variation rarely follows well defined trends; rather

it exhibits a stochastic (i.e., random) character. However, the

stochastic character of many soil properties tends to follow

classic statistical distributions. For example, properties such as

bulk density and effective porosity of soils tend to be normally

districted (Campbell, 1985). Saturated hydraulic conductivity,

in contrast, is often found to follow a log-normal distribution.

characterization of a site, therefore, should be performed in

such a manner as to permit the determination of the statistical

characteristics (i.e., mean and variance) and their spatial

correlations. “

(Continued on page 8)

5
TABLE 1. MEASUREMENT METHODS FOR PRIMARY SOIL CHARACTERISTICS

NEEDED TO SUPPORT CERCLA DECISION-MAKING PROCESS

Bulk density

Soil ph

Texture

Depth to

ground water

I
. .

(ASTM E 119547, 1938)

Continued)
Significant advances have been made in understanding and

describing the spatial variability of soil properties (Neilsen end

Bouma, 1966). Geostatistical methods and techniques (Clark,

1962; Davis, 1966) are available for statistically characterizing

soil properties important to contaminant migration. Information

gained from a geostatistical analysis of data can be used for

three major purposes:

0

●

●

Determining the heterogeneity and complexity of the site;

Guiding the data collection and interpretation effort and thus

identifying areas where additional sampling maybe needed

(to reduce uncertainty by estimating error); and

Providing data for a stochastic modal of fluid flow and contaminant-migration.

One of the geostatistical tools useful to help in the interpolation

or mapping of a site is referred to se kriging (Davis, 1966).

General kriging computer codes are presently available. Application of this type of tool, however, requires an adequate

sample size. As a rule of thumb, 60 or more data points are

needed to construct the semivariogram required for use in

kriging. The benefit of using kriging in site characterization is

that it allows one to take point measurements and estimate soil

characteristics at any point within the domain of interest, suchs as

grid points, for a computer model. Geostatistical packages are

available from the US EPA, Geo-EAS and GEOPACK (Englund

and Sparks, 1988 and Yates and Yates, 1990).

The use of stochastic models in hydrogeology has increased

significantly in recent years. Two stochastic approaches that

have been widely used are the first order uncertainty method

(Dettingerand Wilson, 1981) and Monte Carlo methods (Clifton

et al., 1985; Sager et al., 1986; Eslinger and Sagar, 1988).

Andersson and Shapiro (1983) have compared these two approaches for the case of steady-state unsaturated flow. The

Monte Carlfo methods are more general and easier to implement

than the first order uncertainty methods. However, the Monte

Carlo method is more computationallv intensive, particularlv for . .

multidimensional problems. -

.

(Continued on page 10)

8

Application of stochastic models to hazardous waste Sites has

two main advantages. First, this approach provides a rigorous

way to assess the uncertainty associated with the spatial variability of soil properties. Second,the approach

predictions in terms of the likeihood of outcomes, i.e., probabilproduces model

ity of exceeding water quality standards. The use of models at

hazardous waste sites leads to a thoughtful and objective

treatment of compliance issues and concerns.

In order tb obtain accurate results with models, quality data

types must be used. The issue of quality end confidence in data

can be partially addressed byobtaining as representative data

as possible. Good quality assurance and quality control plans

must be in place for not onl y the acquisition of samples, but also

for the application of the models (van der Heijde, et al., 1989).

Specific soil characterisics vary both laterally and vertically in

an undisturbed soil profile. Different soil characteristics have 

different variances. As an example, the sample size required to

have 95 percent probability of detecting a change of 20 percent

in the mean bulk density at a specific site was 6; however, for

saturated hydraulic conductivity the sample size would need to

be 502 (Jury, 1966). A good understanding of site soil characteristics can help the investigators understand these variations.

This is especially true for most hazardous waste sites because

the soils have often been disturbed, which may cause even

greater variability.

An important aspect of site characterization data and models is

that the modeling process is dynamic, i.e., as an increasing

numberof”simplifying”assumptions are needed,the complexit y

of the models must increase to adequately simulate the additional processes that must be included. Such simplifying assumptions might include an isotropic homogeneous medium or

the presence of only one mobile phase (Waver, et al., 1969).

In order to decrease the numberof assumptions required, there

is usually a need to increase the number of site-specific soil

characteristic data types in a model (seeTable 2);thus providing

greater confidence in the values produced. For complex sites,

an iterative process of initial data collection and evaluation

leading to more data collection and evaluation until an acceptable level of confidence in the evaluation can be reached can be

used.

Table 3 identifies selected unsaturated zone models and their

soil characteristic needs. For specific questions regarding use

and application of the model, the reader should refer to the

associated manuals. Some of these models are also reviewed

by Donigan and Rao (1966) and van der Heijde et al. (1966).

SOIL CHARACTERISTICS DATA TYPES REQUIRED

FOR REMEDIAL ALTERNATIVE SELECTION

Remedial Alternative Selection Procedure

The CERCLA process involves the identification, screening and

analysis of remedial alternatives at uncontrolled hazardous

waste sites (US EPA, 1988c). During screening end analysis,

decision values for process-limiting characteristics for a given

remedial alternative are compared to site-specific values of

those characteristics. If site-specific values are outside the

range required for effective use of a particular alternative, the

alternative is less likely to be selected. Site soil conditions are

critical process-limiting characteristics.

Process Limiting Characteristics

Process-Limiting characteristics are site- and waste-spedfic

data types that are critical to the effectiveness and ability to

implement remedial processes. Often, process-limiting characteristics are descriptors of rate-limiting steps in the overall

remedial process. In some cases, limitations imposed by

process-limiting characteristics can be overcome by adjustment

of soil characteristics such as pH, soil moisture content, temperature and others. In other cases, the level of effort required

to overcome these limitations will preclude use of a remedial

process.

Decision values forprocess limiting characteristics are increasingly available in the literature and may be calculated for

processes where design equstions are known. Process limiting

characteristics are identified and decision values are given for

several vadose zone remedial alternatives in Table 4. For

waste/site characterization, process-limiting characteristics

may be broadly grouped in four categories:

1. Mass transport characteristics

2. Soil reaction characteristics

3. Contaminant properties

4. Engineering characteristics

Thorough soil characterization is required to determine sitespecific values for process-limiting characteristics. Most remedial alternatives will have process-limiting characteristics in

more than one category.

Mass Transport Characteristics

Mass transport is the bulk flow, or advection of fluids through

soil. Mass transport characteristics are used to calculate

potential rates of movement of liquids or gases through soil and

include:

Soil texture

Unsaturated hydraulic conductivity

Dispersivity

Moisture content vs. soil moisture tension

Bulk density

Permeability

Infiltration rate, stratigraphy and others.

Mass transport processes are often process-limiting for both in

situ and extract-and-treat vadose zone remedial alternatives

(Table 4). In situ alternatives frequently use a gas or liquid

mobie phase to move reactants or nutrients through contaminated soil. Alternatively, extract-and-treat processes such as

soil vapor extraction (SVE) or soil flushing use a gas or liquid

mobile phase to move contaminantsto a surface treatment site.

Foreither type o process to be effective, mass transport rates

must be large enough to clean up a site within a reasonable time.

Soil Reaction Characteristics

Soil reaction characteristics describe contaminant-soil interactions. Soil reactions include bio-and physiochemical reactions

that occur between the contaminants and the site soil. Rates of

reactions such as biodegradation, hydrolysis, sorption/desorption, precipitation/dissolution, redox reactions, acid-base

reactions, and others are process-limiting characteristics for

(Continued on page 12)

10

Porosity

many remedial alternatives (Table 4). Soil reaction characteristics include:

Soil

Kd

, specific to the site soils and contaminants

Cation exchange capacity (CEC)

pH

Soil biota

Soil nutrient content

Contamiant abiotic/biological degradation rates

soil mineralogy

Contaminant properties, described below, and others.

reaction characteristics determine the effectiveness of

many remedial alternatives. For example, the ability of a soil to

attenuate metals (typically described by Kd may determine the

effectiveness of an alternative that relies on capping

and natural attenuation to immobilize contaminants.

Soil Contaminant Properties

Contaminant properties are critical to contaminant-soil interactions, contaminant mobility, and to the ability of treatment

technologies to remove, destroy or immobilize contaminants.

important contaminant properties include:

Water volubility

Dielectric constant

Diffusion coefficient

Molecular weight

Vapor pressure

Density

Aqueous solution chemistry, and others.

Soil contaminant properties will determine the effectiveness of

many treatment technques. For example,the aqueous solution

chemistry of metal contaminants often dictates the potential

effectiveness of stabilization/solidification alternatives.

Soil Engineering Characteristics and Properties

Engineering characteristics and properties of the soil relate both

to implementability end effectiveness of the remedial action.

Examples include the ability of the treatment method to remove,

destroy or immobilize contaminants;the costs and difficulties in

installing slurry walls and other containment options at depths

greater than 60 feet; the ability of the site to withstand vehicle

traffic (trafficability); costs and difficulties in deep excavation of

contaminated soil; the ability of soil to be worked for implementation of in situ treatment technologies (tilth); and others.

Knowledge of site-specific engineering characteristics and

Properties is therefore required for analysis of effectivenees end

implementability of remedial alternatives. Engineering characteristics and properties include, but era not limited to:

Erodability

Tilth

Depth to groundwater

Thickness of saturated zone

Depth and total volume of contaminated soil

Bearing capacity, and others.

SUMMARY AND CONCLUSIONS

The goal of the CERCLA RI/FS process is to reach a ROD in a

timely rnanner. Soil characterization is critical to this goal. Soil

characterization provides data for RI/FS tasks including determination of the nature and extent of contamination, risk asassessment, and selection of remedial techniques.

This paper is intended to inform investigators of the data types

required for RI/FS tasks, so that data may be collected as

quickly, efficiently, and cost effectively as possible. This

knowledge should improve the consistency of site evaluations,

improve the ability of OSCs and RPMs to communicate data

needs to site contractors, and aid in the overall goal of reaching

a ROD in a timely manner.

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ASTM, 1987. American Society for Testing and Materials,

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Amoozegar, A. and A. W. Warrick 1986. Hydraulic Conductivity

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[

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K o c

K d

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Bonazountas, M. and J. M. Wagner, 1984. SESOIL- A

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